A Study on Feature Extraction of Surface Defect Images of Cold Steel

Feature extraction is one of the important characteristics used in classifying images. But the extracted features have big numbers and high dimension easily due to various type defects, complicated features and diverse methods of feature. Big numbers and high dimension of features are adverse for feature extraction. The effect of feature extraction decides the effect of image classification directly. According to these problems, experimental investigations are carried out on computer aiming at three typical surface defect images of cold steel strip, and this paper choose the gray features, textural features and Hu invariant moment features as the basis of classification finally. Experimental results demonstrated that features in this paper can be classification basis correctly.